vanbelle1Fit: survivalsvm (ranking approach)
In imbs-hl/survivalsvm: Survival Support Vector Analysis

vanbelle1Fit

R Documentation

survivalsvm (ranking approach)

Description

fits the 'vanbelle1' version of the ranking approach of survival support vector ananlysis.

Usage

vanbelle1Fit(
  X,
  Y,
  delta,
  meth_par = 1,
  kernel_type = "lin_kernel",
  kernel_pars = NA,
  bin_cat = integer(0),
  makediff = makediff3,
  opt_alg = "quadprog",
  sgf_sv = 5,
  sigf = 7,
  maxiter = 40,
  margin = 0.05,
  bound = 10,
  eig.tol = 1e-06,
  conv.tol = 1e-07,
  posd.tol = 1e-08
)

Arguments

`X`	[`matrix(1)`] Matrix of training data points.
`Y`	[`vector(1)`] Vector of survival times.
`delta`	[`vector(1)`] Vector of status: 1 = not censored.
`meth_par`	[numeric(1)] Parameter of regularization.
`kernel_type`	[`character(1)`] Kernel that will be used to fit the model. The handled type are: linear kern ('lin_kern'), additive kernel ('add_kernel'), radial basis kernels ('rbf_kernel' and 'rbf4_kernel') and the polynomial kernel ('poly_kernel').
`kernel_pars`	[`numeric(1)\|vector(1)`] Parameters of kernel, when required.
`bin_cat`	[`vector(1)`] Indexes of binary/categorical varibales
`makediff`	[`character(1)`] String indicating which of `'makediff1'`, `'makediff2'` or `'makediff3'` will be used.
`opt_alg`	[`vector(1)`] Program that will be used to solve the quadratic optimization problem. Either `quadprog` or `ipop`.
`sgf_sv`	[`integer(1)`] Number of decimal digits in the solution of the quadratic optimization problem.
`sigf`	[`integer(1)`] Used by `ipop`. See `ipop` for details.
`maxiter`	[`integer(1)`] Used by `ipop`. See `ipop` for details.
`margin`	[`numeric(1)`] Used by `ipop`. See `ipop` for details.
`bound`	[`numeric(1)`] Used by `ipop`. See `ipop` for details.
`eig.tol`	[`numeric(1)`] Used by `nearPD` for adjusting positive definiteness. See `nearPD` for detail.
`conv.tol`	[`numeric(1)`] Used by `nearPD` for adjusting positive definiteness. See `nearPD` for detail.
`posd.tol`	[`numeric(1)`] Used by `nearPD` for adjusting positive definiteness. See `nearPD` for detail.

Value

[VB1FitObj(1)] object of class VB1FitObj containing elements:

`Alpha`	solution of the quadratic optimization problem,
`Xtrain`	matrix of training data points,
`DifMat`	matrix used to maked differences between neighbor points,
`Kernel`	kernel matrix, an object of class `Kernel`,
`OptMeth`	program used to solve the quadratic optimization problem.